Tables and Figures

Table 1. Summary of conditions, design, and sample sizes of Experiments 1-5, and Skerry et al (2013) (SCS) Experiments 1-5, including sample size (N), what motor training procedures were used (effective sticky mittens, ineffective non-sticky mittens, or none), the goal of the person reaching (changing an object’s state, or picking it up), whether the person acted on the object in a spatiotemporally contingent manner (causal: yes, or no), and whether the person wore a mitten (yes or no). Conditions listed under a single experiment (e.g. Exp 1 and 3) included random assignment to condition. For stimuli, see Fig 1. * indicates direct replication. For stimuli, see Fig 1.

Experiment N Training Goal Habituation Causal Mitten Stimuli
1 20 none state change constrained yes yes H1, T1
1 20 none state change unconstrained yes yes H2, T1
2 20 none state change constrained no yes H3, T2
3* 26 none state change constrained yes yes H1, T1
3* 26 none state change constrained no yes H3, T2
4 20 none pick up constrained yes yes H4, T3
5 20 none pick up constrained yes no H5, T4
SCS 1 20 effective pick up constrained yes yes
SCS 2 20 ineffective pick up constrained yes yes
SCS 3 20 none pick up constrained yes yes
SCS 4* 26 effective pick up constrained yes yes
SCS 5 26 effective pick up unconstrained yes yes

Figure 1. Still frames from videos shown to participants in Experiments 1-5, including stimuli from habituation (H1-H5) and test (T1-T4). In each video, a person reached for and caused a change in an object (H1-H3, T1-T2), or picked up the object (H4-H5, T3-T4), over a barrier (H1- H2, H4-H5) or over empty space (H2, T1-T4). The person either acted on the object by contacting it (H1-H2, H4-H5, T1, T3-T4) or produced the same effect from a distance of 50 pixels, after a 0.5s delay (H3, T2), and either performed these actions while wearing a mitten (H1-H4, T1-T3) or with a bare hand (H5, T4) During test (T1-T4), the person either reached directly for the object on a novel but efficient trajectory (T1-T4, left panel), or in a curvilinear fashion on the familiar but inefficient trajectory (T1-T4, right panel).

Figure 1. Still frames from videos shown to participants in Experiments 1-5, including stimuli from habituation (H1-H5) and test (T1-T4). In each video, a person reached for and caused a change in an object (H1-H3, T1-T2), or picked up the object (H4-H5, T3-T4), over a barrier (H1- H2, H4-H5) or over empty space (H2, T1-T4). The person either acted on the object by contacting it (H1-H2, H4-H5, T1, T3-T4) or produced the same effect from a distance of 50 pixels, after a 0.5s delay (H3, T2), and either performed these actions while wearing a mitten (H1-H4, T1-T3) or with a bare hand (H5, T4) During test (T1-T4), the person either reached directly for the object on a novel but efficient trajectory (T1-T4, left panel), or in a curvilinear fashion on the familiar but inefficient trajectory (T1-T4, right panel).


Figure 2. Looking time in towards the efficient versus inefficient reach (bottom), and proportion looking towards the inefficient reach (top) at test across Experiments 1-5 (n=152) and across Experiments 1-5 in Skerry et al. (2013) (n=112). Labels above each panel list the experiment name (Exp. 1-5, SCS Exp. 1-5), type of motor training (none, ineffective non-sticky mittens, or effective sticky mittens), type of action during habituation (constrained or unconstrained by a barrier), goal (state.change or pick.up), whether her actions appeared to be causal (yes.causal or no.causal), whether the actress wore a mitten (yes.mitten or no.mitten), and stimuli listed in Figure 1. Error bars around means indicate within-subjects 95% confidence intervals (bottom) and bootstrapped 95% confidence intervals (top). Individual points (top) or pairs of points (bottom) indicate data from a single participant. Horizontal bars within boxes indicate medians, and boxes indicate the middle 2 quartiles of data. Violin plots (top) indicate distribution of data, area scaled proportionally to the number of observations.


Results (Main Text)

Infants’ analysis of causal vs non-causal actions

Experiment 1

In Experiment 1 (N=40; 20 per condition), we asked whether 3-month-old infants (M=107.675 days, range=91-122, 23 female) expect a person to reach out and cause an object to change state efficiently. We randomly assigned infants to repeatedly view video clips of a person who reached over a barrier and appeared to cause an object to light up by touching it (H1), or to view the same reaches with the barrier beyond the goal object, out of the person’s way (H2) (a motion that does not appear intentional to infants (Gergely et al., 1995)). Then, infants in both conditions viewed the same pair of alternating test events, in which the barrier was removed and the person reached either efficiently on a novel, direct path or inefficiently on a familiar, indirect path (T1). A mixed effects model, including a fixed interaction between habituation and test event and a random intercept for participant identity, revealed that infants responded differently to the test events across these two habituation conditions, [0.273,0.732], ß=0.781, B(SE)=0.502(0.114), p<.001, two-tailed, 2 participants excluded on the basis of Cook’s Distance. Contrasts from this model revealed that when the person’s reaches were initially constrained by a barrier, infants looked longer at the inefficient action (M=15.448s, SE=0.658) than the efficient action (M=12.368s, SE=0.658) at test, [0.396,1.139], ß=1.194, B(SE)=0.768(0.185), p<.001, one-tailed. Critically, this looking preference cannot be attributed to low-level responses to the curvilinear reach, because infants in the other condition of the experiment, who were randomly assigned to habituate to otherwise identical videos in which the the barrier was behind the object (H2),looked marginally shorter at the inefficient (M=8.788s, SE=0.738) and efficient (M=10.104s, SE=0.738) actions, [-0.343,-0.017], ß=-0.28, B(SE)=-0.18(0.081), p=0.016, one-tailed.

Experiment 2

In Experiment 2 (N=20), pre-registered at https://osf.io/a5byn/, we asked whether infants’ causal analysis of an action is critical to their understanding of this action as intentional, as suggested by past studies of causal perception (Michotte 1963; Muentener and Carey 2010; Leslie 1984). We tested whether infants’ expectations from Experiment 1 depended on their construal of the person as a causal agent (an agent contacting an object, thereby changing its state) or on lower-level scene features (an agent reaching towards an object that happens to illuminate), by manipulating the spatiotemporal continuity of this action. Infants (M=106.7 days, range=93-121, 12 female) were habituated to videos identical to H1, except that the person’s hand stopped 50 pixels above the object (approximately 2 cm on the presentation screen), and the object illuminated after a 0.5 second delay. At test, the person reached efficiently or inefficiently in the absence of the barrier, with the same spatiotemporal gap as in habituation trials (T2). We found that infants looked equally between the inefficient (M=15.306s, SE=1.123) and efficient (M=16.38s, SE=1.123) reach, [-0.191,0.301], ß=0.096, B(SE)=0.055(0.119), p=0.649, two-tailed, mixed effects model with trial type as fixed effect and participants as a random intercept, a result that differed from infants’ responses to the causally effective reaches in Experiment 1 (H1), [-0.623,-0.003], ß=-0.547, B(SE)=-0.313(0.154), p=0.049, two-tailed, mixed effects model with fixed interaction between causality and trial type and participants as a random intercept.

Experiment 3

Experiment 3 (N=52; 26 per condition), pre-registered at https://osf.io/f2hvd/, attempted to replicate the findings from Experiments 1 and 2 that infants expect causally effective reaches to be efficient, but do not expect efficiency when presented with same actions that are not spatiotemporally continuous. We randomly assigned infants (M=107.154 days, range=92-121, 21 female) to H1 and T1, or H3 and T2: a design that enables us to directly compare infants’ responses to causal vs non-causal actions, using experimenters who are blind to both condition and test event information. Our findings replicated those of the previous two studies: Infants’ tendency to view the agent’s actions as efficiently directed to the goal object again depended on the presentation of actions that elicit an impression of contact causality, in which the agent’s hand contacted the object at the time of the object’s change of state, [-0.815,-0.184], ß=-0.729, B(SE)=-0.5(0.158), p=0.003, two-tailed, mixed effects model with fixed interaction of causality and test event and random intercept for participants. As in Experiment 1, infants looked longer at the inefficient reach (M=12.166s, SE=0.588) than the efficient reach (M=7.791s, SE=0.588) when the person’s actions were causally effective, [0.211,0.66], ß=0.635, B(SE)=0.436(0.112), p<.001, one-tailed, and as in Experiment 2, infants looked equally to the inefficient (M=11.395s, SE=0.818) and efficient (M=12.888s, SE=0.818) reaches when the spatiotemporal gap between her hand the the object’s illumination suggested that she did not cause this event, [-0.289,0.16], ß=-0.094, B(SE)=-0.064(0.112), p=0.284, one-tailed. Together, Experiments 1-3 show that pre-reaching infants apply the principle of efficiency (Gergely & Csibra, 2003) to reaching actions that they themselves have never experienced, and that they only apply this principle to actions that appear to cause changes in the world.

Infants’ analysis of entrainment actions

Experiments 4 and 5

Why do infants succeed in these experiments without motor training, yet fail in the experiments of SCS? First, pre-reaching infants may struggle to understand the causal structure of reaching for and retrieving an object without the relevant motor experience. Second, pre-reaching infants may not interpret the reach of a mittened hand, one that looks different from most hands they see, as intentional (Guajardo & Woodward, 2004), causal, and directed to a particular object, without the relevant experience of observing and experiencing their own mittened hands acting causally towards a specific set of objects during training.

To ask whether surface properties of the hand reaching affect infants’ interpretation of the intentionality of these reaches, we ran two additional experiments. In Experiment 4 (N=20), infants (M=107.9 days, range=92-122, 11 female) were habituated to and tested on events where a person reach for and pick up an object identical to those from Experiments 1-3 while wearing the same mitten (H4, T3). In Experiment 5 (N=20), infants (M=107.95 days, range=93-120, 12 female) saw almost identical videos to those from Experiment 4 except that the person reached with a bare hand (H5, T4).

In Experiment 5, infants looked longer at the inefficient (M=9.715s, SE=0.474) than the efficient (M=18.029s, SE=0.643) reach of the bare hand, [0.008,0.331], ß=0.296, B(SE)=0.17(0.08), p=0.02, one-tailed, but in Experiment 4, they did not distinguish the inefficient (M=18.029s, SE=0.643) from the efficient (M=16.844s, SE=0.643) action of the mittened hand [-0.083,0.232], ß=0.13, B(SE)=0.074(0.078), p=0.172, one-tailed. However, these two patterns of looking did not differ from each other, [-0.128,0.319], ß=0.167, B(SE)=0.095(0.111), p=0.396, two-tailed, mixed effects model with fixed interaction between mitten and test trial, random intercept for participants, excluding 3 influential participants on the basis of Cook’s Distance.

We also compared these results against those from SCS Experiment 3, wherein infants received no mittens training and viewed a person reaching with a mittened hand. The results of Experiment 5 (no mitten) differed from those in SCS Experiment 3 (mitten), [0.047,0.547], ß=0.539, B(SE)=0.297(0.124), p=0.022, two-tailed, mixed effects model with fixed interaction between experiment and test event and random intercept for participants, one influential participant excluded on the basis of Cook’s Distance, whereas the results from Experiment 4 (mitten) only marginally differed from those in SCS Experiment 3 (mitten), [-0.021,0.47], ß=0.43, B(SE)=0.224(0.122), p=0.074, two-tailed, mixed effects model with fixed interaction between experiment and test events and random intercept for participants, 2 influential participants excluded on the basis of Cook’s Distance. This finding accords with reports that young infants trained with mittens view an agent’s reach as goal-directed only if the agent wears the same mittens and interacts with the same objects as they did during training (Gerson & Woodward, 2014; Woodward, 2008). Nevertheless, the differences in infants’ responses to gloved and ungloved hands are not robust in our studies and merit further investigation.

Results across Experiments 1-5 and SCS

Across Experiments 1-5, we found that pre-reaching infants apply expectations of efficient action to a person who pursues the goal of causing a change in an object while wearing a mitten, but do not apply the same expectation to the same person wearing the same mitten when she picks up the same object. Thus, we suggest that one key difference between the state change events we used in the present experiments, and the pickup events used in SCS and Experiments 4-5, is the causal transparency of these actions: Three-month-old infants do not know how to reach for and grasp objects, and thus may struggle to understand how grasping an object could cause it to rise and move closer to the person reaching for it, thereby fulfilling the goal of the agent to retrieve it. Indeed, infants’ own ability to produce power grasps (the actions tested in Experiment 4 and 5 and in SCS) predicts their ability to represent such grasps as directed towards an object (Bakker et al., 2015). Although the infants in our experiments will not master these grasping actions until around 5 months of age (von Hofsten, 1980), these infants may nevertheless possess the intuition that causal agents behave efficiently, an expectation they apply to events in which an object changes state on contact with an agent’s hand.

To assess the unique effects of our experimental manipulations and those from SCS, we performed an analysis over these two papers (total N=264, 12 conditions). Our analytic approach allows us to assess the independent effects of 5 manipulations (motor training, goal, habituation, causal information, and surface properties of the hand), on infants’ expectations about efficient reaching, while controlling participant variables like age and sex, and also modeling the nested structure of the data (e.g. looks clustered within experiments and within papers). For ease of interpretation, we use average proportion looking to the inefficient action in this analysis, following SCS.


Table 2. Regression table for model investigating predictors of sensitivity to action efficiency across Experiment 1-5 and all experiments from Skerry et al. (2013) (total N=264, 247 included in final analysis, 17 excluded on the basis of Cook’s Distance). Dependent measure is proportion looking towards the inefficient reach, averaged across 3 test trials during test. Categorical predictors were coded using sum contrasts, and fixed effects from the model should therefore be interpreted with respect to the grand mean (i.e. with respect to 0). Model formula: prop.ineff.all ~ training + goal + hab + causal + mitten + (1|experiment) + (1|ageday) + (1|sex) + (1|paper).

Standardized Estimate (ß) Estimate (B) Standard Error (SE) df t p 95% CI (Lower) 95% CI (Upper)
(Intercept) -0.340 0.488 0.019 2.19 25.28 0.001 0.457 0.523
effective training 0.558 0.049 0.011 7.32 4.31 0.003 0.027 0.069
ineffective training -0.354 -0.031 0.015 8.70 -2.08 0.068 -0.060 -0.005
state change goal 0.397 0.035 0.010 4.24 3.66 0.020 0.020 0.053
constrained habituation 0.407 0.036 0.008 9.61 4.54 0.001 0.021 0.051
causally effective 0.501 0.044 0.009 20.54 5.08 0.000 0.027 0.060
mitten -0.232 -0.021 0.012 7.39 -1.65 0.140 -0.045 0.000

Figure 3. Effect plots for model investigating predictors of sensitivity to action efficiency across Experiments 1-5 and Skerry et al. (2013). Each point shows estimates of effects at each level of all categorical predictors. Error bars indicate 95% confidence intervals. See Table 2 for full results.


This analysis confirms that first-person action experience is not the only way to enhance infants’ appreciation of the causal and intentional aspects of action. We found that infants’ expectations were stronger when the observed action was spatiotemporally continuous its effect (i.e., appeared to be causal), [0.027,0.06], ß=0.501, B(SE)=0.044(0.009), p<.001, two-tailed, when infants received effective motor training (sticky mittens), relative to no training [0.027,0.069], ß=0.558, B(SE)=0.049(0.011), p=0.003, two-tailed, when the observed agent’s actions were constrained by a barrier and were efficiently adapted to that barrier, relative to the same actions that were unconstrained by a barrier, [0.021,0.051], ß=0.407, B(SE)=0.036(0.008), p=0.001, two-tailed, and when the agent pursued a state change goal, relative to a pickup goal, [0.02,0.053], ß=0.397, B(SE)=0.035(0.01), p=0.02, two-tailed. We also found that infants’ expectations were marginally negatively affected when they received ineffective motor training (non-sticky mittens), relative to no training, [-0.06,-0.005], ß=-0.354, B(SE)=-0.031(0.015), p=0.068, two-tailed, and were unaffected when the actor wore a mitten, relative to no mitten [-0.045,0], ß=-0.232, B(SE)=-0.021(0.012), p=0.14, two-tailed.

Reliability (Methods Section)

To assess reliability, 50% of test trials from participants across Experiments 1-5 (132 participants, 456 trials) were randomly selected and coded by additional researchers who were unaware of experimental condition, and test trial order. The intraclass correlation coefficient (ICC) between the original data, and this newly coded data, was 0.968 [0.955, 0.978], 0.963 [0.938, 0.977], 0.936 [0.911, 0.954], 0.969 [0.946, 0.982], 0.969 [0.943, 0.982], for Experiments 1 through 5, respectively.

Supplemental Results

Exclusion info

Table S1. Tally of infants who participated in Experiments 1-5 but were excluded in our final sample. These exclusion criteria were set prior to the start of data collection, but vary slightly by experiment (e.g. we relaxed our definition of inattentiveness from excluding all data from a participant if they missed a test trial in Experiment 1, to excluding data from just that trial in Experiments 2-5).

Experiment Fussiness Inattentiveness Caregiver Interference Experimenter/Coding Error Technical Failure Total
Exp.1 9 5 1 12 3 30
Exp.2 0 0 0 2 0 2
Exp.3 6 0 0 2 0 8
Exp.4 7 0 0 2 0 7
Exp.5 6 0 0 1 2 9
Total 28 5 1 19 5 50

Distribution of Looks

Figure S1. Density plot of looking times during test across Experiments 1-5, and Experiments 1-5 from Skerry et al. (2013) (N=264). Maximum-likelihood fitting revealed that the lognormal distribution (log likelihood=-1720.509) provides a better fit to these data than the normal distribution (log likelihood=-1842.196).


Reliability

Figure S2. Discrepancy between original and new coding of looking times during test trials in seconds.


Attention during habituation across Exp 1-5

Figure S3. Total looking time in seconds during habituation across Experiment 1-5. Error bars around means indicate bootstrapped 95% confidence intervals. Individual points indicate data from a single participant. Horizontal bars within boxes indicate medians, and boxes indicate the middle 2 quartiles of data. Violin plots in indicate distribution of data, area scaled proportionally to the number of observations.


Figure S4. Looking time in seconds during each habituation trial across Experiment 1-5. Curves with 95% confidence interval ribbons indicate smoothed conditional means, generated using the loess method. Connected points indicate data from a single participant.


Table S2. Regression table for mixed effects model analyzing the effect of age, sex, order of test events, habituation condition, goal, mitten, and causal information on habituation, controlling for variations across Experiments 1-5. Model formula: total_hab ~ ageday + sex + first.test + hab + goal + mitten + causal + (1|experiment)

Standardized Estimate (ß) Estimate (B) Standard Error (SE) df t p 95% CI (Lower) 95% CI (Upper)
(Intercept) -0.208 343.171 76.54 151.82 4.483 0.000 192.192 494.168
Age in Days -0.233 -2.058 0.68 147.57 -3.026 0.003 -3.400 -0.714
Sex 0.066 5.203 6.11 148.69 0.852 0.396 -6.916 17.274
First Test Event -0.006 -0.439 6.00 146.69 -0.073 0.942 -12.270 11.393
Habituation 0.222 17.590 11.03 131.60 1.595 0.113 -6.441 41.220
Goal 0.007 0.589 16.02 6.18 0.037 0.972 -0.777 50.348
Mitten 0.126 9.996 19.02 5.73 0.525 0.619 8.336 50.922
Causal -0.055 -4.379 9.08 75.38 -0.482 0.631 -5.024 3.212

To ask whether infants’ attention during habituation was affected by experimental manipulations across Experiment 1-5 (constrained vs unconstrained habituation, state change vs pickup goal, mitten vs no mitten, and causally contingent vs noncontigent action), and varied by gender and age, we fit a mixed effects model on these fixed effects and experiment (1-5) as a random intercept. We found that the only robust predictor of attention during habituation was age, [-3.4,-0.714], ß=-0.233, B(SE)=-2.058(0.68), p=0.003, two-tailed, such that older infants looked for a shorter time overall than younger infants.

Exploring effect of test trial order, attention during habituation, age in days, and sex across Exp 1-5

To explore the additional effects of test trial order (inefficient or efficient first), attention during habituation, age in days, and sex on attention during test, we ran one linear model per experiment including an interaction between test event order and test event in Experiments 2, 4, and 5, an interaction between these factors and habituation in Experiment 1, and an interaction between these factors and causal contingency in Experiment 3.

Regression tables for each of these models is below. In general, we find no effect of sex or age, and we consistently find that infants who look longer during habituation also are more attentive during test. See tables below.

In Experiment 1, we also find that infants randomly assigned to habituate to a rational agent look longer overall at test, [0.022,0.28], ß=0.233, B(SE)=0.151(0.064), p=0.024, two-tailed, and that infants randomly assigned to view the efficient reach first look longer overall at test, [0.018,0.276], ß=0.227, B(SE)=0.147(0.064), p=0.027, two-tailed.

In Experiment 2, we also find that infants randomly assigned to look at the efficient reach first look longer overall at test, [-0.339,-0.072], ß=-0.356, B(SE)=-0.205(0.067), p=0.006, two-tailed.


Tables S3-S7. Regression tables from exploratory models in Experiments 1-5. Dependent measure is log-tranforming looking times at test, averaged across 3 test pairs. Categorical predictors were coded using sum contrasts, and fixed effects from the model should therefore be interpreted with respect to the grand mean (i.e. with respect to 0). Model formulas are listed above each table. See Figures S4-S8.

Figures S4-S8. Effect plots for model investigating exploratory and hypothesis-driven predictors of sensitivity to action efficiency across Experiments 1-5. Each point shows estimates of effects at each level of all categorical predictors. Error bars and ribbons indicate 95% confidence intervals. See Tables S3-S7 for full results.

Experiment 1

Model formula: loglook ~ hab * type * first.test + total_hab + sex + ageday + (1|subj_id)

Standardized Estimate (ß) Estimate (B) Standard Error (SE) df t p 95% CI (Lower) 95% CI (Upper)
Intercept 0.012 2.579 0.941 40 2.739 0.009 0.689 4.469
Habituation 0.233 0.151 0.064 40 2.350 0.024 0.022 0.280
Test Event 0.050 0.032 0.033 40 0.978 0.334 -0.034 0.099
First Test Event 0.227 0.147 0.064 40 2.289 0.027 0.018 0.276
Attention During Habituation 0.463 0.003 0.001 40 3.564 0.001 0.001 0.004
Sex -0.082 -0.053 0.065 40 -0.815 0.420 -0.185 0.078
Age in Days -0.113 -0.007 0.008 40 -0.923 0.362 -0.023 0.009
Habituation:Test Event 0.149 0.096 0.033 40 2.923 0.006 0.030 0.163
Habituation:First Test Event 0.052 0.034 0.064 40 0.529 0.600 -0.094 0.161
Test Event:First Test Event -0.069 -0.045 0.033 40 -1.354 0.183 -0.111 0.022
Habituation:Test Event:First Test Event -0.002 -0.001 0.033 40 -0.032 0.974 -0.067 0.065

Experiment 2

Model formula: loglook ~ type * first.test + total_hab + sex + ageday + (1|subj_id)

Standardized Estimate (ß) Estimate (B) Standard Error (SE) df t p 95% CI (Lower) 95% CI (Upper)
Intercept -0.022 2.680 0.780 20 3.434 0.003 1.074 4.286
Test Event -0.048 -0.028 0.060 20 -0.464 0.648 -0.148 0.093
First Test Event -0.356 -0.205 0.067 20 -3.045 0.006 -0.339 -0.072
Attention During Habituation 0.502 0.003 0.001 20 4.146 0.000 0.002 0.005
Sex 0.110 0.064 0.064 20 0.999 0.330 -0.063 0.190
Age in Days -0.085 -0.006 0.007 20 -0.772 0.449 -0.020 0.009
Test Event:First Test Event -0.036 -0.021 0.060 20 -0.352 0.728 -0.142 0.100

Experiment 3

Model formula: loglook ~ causal * type * first.test + total_hab + sex + ageday + (1|subj_id)

Standardized Estimate (ß) Estimate (B) Standard Error (SE) df t p 95% CI (Lower) 95% CI (Upper)
Intercept 0.012 2.310 0.897 52 2.576 0.013 0.519 4.101
Causal 0.097 0.067 0.073 52 0.919 0.363 -0.078 0.212
Test Event 0.135 0.093 0.038 52 2.444 0.018 0.017 0.169
First Test Event -0.063 -0.043 0.071 52 -0.602 0.550 -0.185 0.099
Attention During Habituation 0.428 0.005 0.001 52 4.054 0.000 0.003 0.008
Sex 0.065 0.044 0.075 52 0.594 0.555 -0.105 0.194
Age in Days -0.092 -0.007 0.008 52 -0.830 0.410 -0.023 0.010
Causal:Test Event -0.182 -0.125 0.038 52 -3.292 0.002 -0.201 -0.049
Causal:First Test Event 0.052 0.036 0.072 52 0.503 0.617 -0.107 0.179
Test Event: First Test Event -0.115 -0.079 0.038 52 -2.074 0.043 -0.155 -0.003
Causal:Test Event:First Test Event 0.004 0.003 0.038 52 0.078 0.938 -0.073 0.079

Experiment 4

Model formula: loglook ~ type * first.test + total_hab + sex + ageday + (1|subj_id)

Standardized Estimate (ß) Estimate (B) Standard Error (SE) df t p 95% CI (Lower) 95% CI (Upper)
Intercept -0.008 1.907 1.051 20 1.815 0.085 -0.255 4.070
Test Event 0.020 0.010 0.040 20 0.247 0.807 -0.073 0.093
First Test Event -0.190 -0.093 0.077 20 -1.215 0.239 -0.252 0.065
Attention During Habituation 0.650 0.005 0.001 20 4.163 0.000 0.002 0.007
Sex 0.079 0.039 0.073 20 0.533 0.600 -0.111 0.188
Age in Days 0.019 0.001 0.010 20 0.130 0.898 -0.018 0.021
Test Event:First Test Event -0.201 -0.099 0.040 20 -2.453 0.023 -0.182 -0.016

Experiment 5

Model formula: loglook ~ type * first.test + total_hab + sex + ageday + (1|subj_id)

Standardized Estimate (ß) Estimate (B) Standard Error (SE) df t p 95% CI (Lower) 95% CI (Upper)
Intercept -0.024 0.901 1.221 20 0.738 0.469 -1.611 3.414
Test Event 0.148 0.074 0.041 20 1.782 0.090 -0.011 0.158
First Test Event 0.052 0.026 0.081 20 0.322 0.751 -0.140 0.192
Attention During Habituation 0.596 0.005 0.001 20 3.578 0.002 0.002 0.008
Sex 0.118 0.059 0.080 20 0.736 0.470 -0.105 0.222
Age in Days 0.071 0.005 0.011 20 0.429 0.673 -0.017 0.027
Test Event:First Test Event -0.035 -0.017 0.041 20 -0.419 0.680 -0.102 0.068